February 2026

arXiv:2602.15838v1 Announce Type: new Abstract: Multi-agent trajectory optimization with dense interaction networks require solving large coupled QPs at control rates, yet existing solvers fail to simultaneously exploit temporal structure, agent decomposition, and iteration similarity. One usually treats multi-agent problems monolithically when using general-purpose QP solvers (OSQP, MOSEK), which encounter scalability difficulties with agent count. Structure-exploiting solvers (HPIPM) leverage temporal structure through Riccati recursion but can be vulnerable to dense coupling constraints. We introduce TurboADMM, a specialized single-machine QP […]

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arXiv:2602.15837v1 Announce Type: new Abstract: Autonomous driving systems (ADS) are safety-critical and require rigorous testing before public deployment. Simulation-based scenario testing provides a safe and cost-effective alternative to extensive on-road trials, enabling efficient evaluation of ADS under diverse and high-risk conditions. However, existing approaches mainly evaluates the scenarios based on their proximity to collisions and focus on scenarios already close to collision, leaving many other hazardous situations unexplored. To bridge this, we introduce a collision-related concept of conflict […]

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arXiv:2602.15836v1 Announce Type: new Abstract: Large Action Models (LAMs) have shown immense potential in autonomous navigation by bridging high-level reasoning with low-level control. However, deploying these multi-billion parameter models on edge devices remains a significant challenge due to memory constraints and latency requirements. In this paper, we propose EdgeNav-QE, a novel framework that integrates Quantized Low-Rank Adaptation (QLoRA) with a dynamic early-exit (DEE) mechanism to optimize LAMs for real-time edge navigation. By quantizing the backbone to 4-bit precision […]

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arXiv:2602.15835v1 Announce Type: new Abstract: This paper proposes a methodology for identifying evaluation items for practical dialogue systems. Traditionally, user satisfaction and user experiences have been the primary metrics for evaluating dialogue systems. However, there are various other evaluation items to consider when developing and operating practical dialogue systems, and such evaluation items are expected to lead to new research topics. So far, there has been no methodology for identifying these evaluation items. We propose identifying evaluation items […]

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arXiv:2602.15834v1 Announce Type: new Abstract: We introduce a unified framework that combines nonlinear dynamics, perceptual psychophysics and high frequency haptic rendering to enhance realism in surgical simulation. The interaction of the surgical device with soft tissue is elevated to an augmented state space with a Koopman operator formulation, allowing linear prediction and control of the dynamics that are nonlinear by nature. To make the rendered forces consistent with human perceptual limits, we put forward a Bayesian calibration module […]

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arXiv:2602.15833v1 Announce Type: new Abstract: Virtual reality (VR) glove technology is increasingly important for professional training, industrial applications, and teleoperation in hazardous environments, since it enables more natural and immersive interactions than controllers. However, current solutions face a trade-off: high-precision gloves lack haptic feedback, while haptic gloves suffer from poor accuracy. Existing studies have mainly focused on developing new glove prototypes or optimizing only one type of glove, without addressing the integration of both features. Our work presents […]

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arXiv:2602.15832v1 Announce Type: new Abstract: Existing user simulations, where models generate user-like responses in dialogue, often lack verification that sufficient user personas are provided, questioning the validity of the simulations. To address this core concern, this work explores the task of identifying relevant but unknown personas of the simulation target for a given simulation context. We introduce PICQ, a novel dataset of context-aware choice questions, annotated with unknown personas (e.g., ”Is the user price-sensitive?”) that may influence user […]

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arXiv:2602.15831v1 Announce Type: new Abstract: AI agents are increasingly deployed as autonomous systems capable of planning, tool use, and multi-agent collaboration across complex tasks. However, existing agent-related protocols focus on agent-to-agent interactions, leaving humans as external observers rather than integrated participants within the agent systems. This limitation arises from the lack of a standardized mechanism for agents to discover, address, and interact with humans across heterogeneous messaging platforms. In this paper, we propose the A2H (Agent-to-Human) protocol, a […]

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The Early Days of Infrastructure Operations Imagine you’re the person responsible for managing and maintaining the servers for a company’s website or application. This used to be a simple job, but with technological advancements, infrastructure management has become more complex. In the early days, system administrators often logged into servers manually via SSH (Secure Shell) to configure servers, install software, or solve problems. SSH: The Initial Solution SSH changed everything in the 1990s. Before SSH, people had to […]

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